Can we truly transfer an actor's genuine happiness to avatars? An investigation into virtual, real, posed and spontaneous faces - Peres, Vitor Miguel Xavier; Dal Molin, Greice Pinho; Musse, Soraia Raupp (Anais do Simpósio Brasileiro de Jogos e Entretenimento Digital (SBGames); 2023: Anais do XXII Simpósio Brasileiro de Jogos e Entretenimento Digital, 2023)
“A look is worth a thousand words” is a popular phrase. And why is a simple look enough to portray our feelings about something or someone? Behind this question are the theoretical foundations of the field of psychology regarding social cognition and the studies of psychologist Paul Ekman. Facial expressions, as a form of non-verbal communication, are the primary way to transmit emotions between human beings. The set of movements and expressions of facial muscles that convey some emotional state of the individual to their observers are targets of studies in many areas. Our research aims to evaluate Ekman’s action units (AU) in datasets of real human faces, posed and spontaneous, and virtual human faces resulting from transferring real faces into Computer Graphics (CG) faces. In addition, we also conducted a case study with specific movie characters, such as She-Hulk and Genius. We intend to find differences and similarities in facial expressions between real and CG datasets, posed and spontaneous faces, and also to consider the actors’ genders in the videos. This investigation can help several areas of knowledge, whether using real or virtual human beings, in education, health, entertainment, games, security, and even legal matters. Our results indicate that AU intensities are greater for posed than spontaneous datasets, regardless of gender. Furthermore, there is a smoothing of intensity up to 80% for AU6 and 45% for AU12 when a real face is transformed into CG.